Predicting client engagement by Behavioral modeling - QC-104
Preferred Disciplines: Behavioral Finance, Behavioral Economics or Behavioral Science; Master’s level or above
Project length: 4 to 12 months
Desired start date: As soon as possible
Location: Montreal, Quebec
Preferences: No preferences for language
Start-up fintech company revolutionizing digital customer engagement
The acquisition of products and services, the adoption of new functionalities in the digital world requires trust and clarity. Even when people would benefit from using a function or purchasing a product, their knowledge on about the product, their mood, their recent transactions and many other factors will influence their decision making.
This project will attempt to evolve an existing behavioral model for interactions and recommendations maximizing the value (real and perceived) for the users and their providers. Influence the decision making of the users nudging them towards the best decision in terms of value to them.
This research will be performed on more than 3 million active users belonging to a service provider.
Background and required skills
Several tasks need to be accomplished and challenges overcome by the team of which the researcher will be a part including:
- Identify factors that influence the decision making in a concrete digital environment
- Determine if and how trust levels can be evaluated and their impact on the acceptance by the users of future recommendations
- Create a model to determine when (based on influencing factors) and how to present recommendations and interactions to the users
- Create a model to measure pontential perceived value of recommendation for different users
- Create a machine learning algorithm to adapt to the different users
- Find the best technologies to suit those goals
- To be determined
Expertise and Skills Needed:
Behavioral Economics or science; experience with statistics techniques and tools preferred
For more info or to apply to this applied research position, please
- Check your eligibility and find more information about open projects.
- Complete this webform. You will be asked to upload your CV. Remember to indicate the title of the project(s) you are interested in and obtain your professor’s approval to proceed!
Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform or directly to Jean-Philippe Valois at, firstname.lastname@example.org